This bar plot shows the number of orders placed in each aisle.
This box plot shows the distribution of days since prior order by department.
This line plot shows the number of orders placed throughout the day by department.
---
title: "Dashboard"
output:
flexdashboard::flex_dashboard:
orientation: columns
vertical_layout: fill
source: embed
---
```{r setup, include=FALSE}
library(flexdashboard)
library(tidyverse)
library(p8105.datasets)
library(plotly)
```
```{r}
data("instacart")
instacart1 =
instacart %>%
select(order_id, product_id, user_id, order_dow, order_hour_of_day, days_since_prior_order, product_name, aisle_id, aisle, department_id, department) %>%
sample_n(5000)
```
Column {data-width=650}
-----------------------------------------------------------------------
### Chart A
This bar plot shows the number of orders placed in each aisle.
```{r}
instacart1 %>%
count(aisle) %>%
mutate(aisle = factor(aisle),
aisle = fct_reorder(aisle, n)) %>%
plot_ly(
x = ~aisle, y = ~n, color = ~aisle, type = "bar",
colors = "viridis"
)
```
Column {data-width=350}
-----------------------------------------------------------------------
### Chart B
This box plot shows the distribution of days since prior order by department.
```{r}
instacart1 %>%
mutate(department = factor(department),
department = fct_reorder(department, days_since_prior_order)) %>%
plot_ly(
x = ~department, y = ~days_since_prior_order, color = ~department, type = "box",
colors = "viridis"
)
```
### Chart C
This line plot shows the number of orders placed throughout the day by department.
```{r}
instacart1 %>%
group_by(department) %>%
count(order_hour_of_day) %>%
plot_ly(
x = ~order_hour_of_day, y = ~n, color = ~department, type = "scatter",
mode = "lines", colors = "viridis"
)
```